An eight-year snapshot of geospatial cancer research (2002–2009): clinico-epidemiological and methodological findings and trends

Boulos, Dina N. K.; Ghali, Ramy R.; Ibrahim, Ezzeldin M.; Boulos, Maged N. Kamel; Abdelmalik, Philip

doi:10.1007/s12032-010-9607-z

Cited by 15 publications

(3 citation statements)

References 145 publications

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“…Due to a growing awareness of the impact of residential location on health and the development of more sophisticated analysis tools, the value of geospatial research in cancer is increasing. 42 With the availability of geocoded addresses and the use of GAMs, we identified disparities within the state of California where women were more or less at risk of non-adherent care, despite adjusting for numerous important factors and further showed that the impact of location depended on stage at diagnosis. This methodology was previously used to examine late-stage OC survival disparities across California census tracts.…”

Section: Discussionmentioning

confidence: 99%

Contribution of Geographic Location to Disparities in Ovarian Cancer Treatment

Villanueva

Chang²,

Bartell

et al. 2019

Journal of the National Comprehensive Cancer Network

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Background: More than 14,000 women in the United States die of ovarian cancer (OC) every year. Disparities in survival have been observed by race and socioeconomic status (SES), and vary spatially even after adjusting for treatment received. This study aimed to determine the impact of geographic location on receiving treatment adherent to the NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for OC, independent of other predictors. Patients and Methods: Women diagnosed with all stages of epithelial OC (1996–2014) were identified through the California Cancer Registry. Generalized additive models, smoothing for residential location, were used to calculate adjusted odds ratios (ORs) and 95% CIs for receiving nonadherent care throughout California. We assessed the impact of distance traveled for care, distance to closest high-quality hospital, race/ethnicity, and SES on receipt of quality care, adjusting for demographic and cancer characteristics and stratifying by disease stage. Results: Of 29,844 patients with OC, 11,419 (38.3%) received guideline-adherent care. ORs for nonadherent care were lower in northern California and higher in Kern and Los Angeles counties. Magnitudes of associations with location varied by stage (OR range, 0.45–2.19). Living farther from a high-quality hospital increased the odds of receiving nonadherent care (OR, 1.18; 95% CI, 1.07–1.29), but travel >32 km to receive care was associated with decreased odds (OR, 0.76; 95% CI, 0.70–0.84). American Indian/other women were more likely to travel greater distances to receive care. Women in the highest SES quintile, those with Medicare insurance, and women of non-Hispanic black race were less likely to travel far. Patients who were Asian/Pacific Islander lived the closest to a high-quality hospital. Conclusions: Among California women diagnosed with OC, living closer to a high-quality center was associated with receiving adherent care. Non-Hispanic black women were less likely to receive adherent care, and women with lower SES lived farthest from high-quality hospitals. Geographic location in California is an independent predictor of adherence to NCCN Guidelines for OC.

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Section: Discussionmentioning

confidence: 99%

Contribution of Geographic Location to Disparities in Ovarian Cancer Treatment

Villanueva

Chang²,

Bartell

et al. 2019

Journal of the National Comprehensive Cancer Network

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“…By actively approaching and engaging these individuals within the community, HealthStreet enables historically “hidden” or disenfranchised populations to be more effectively reached and referred to programs, services, and research opportunities [9]. Utilization of spatial statistics combined with these community-engaged data collection efforts represents a potential method to guide community-engagement outreach efforts to reach underrepresented populations who may benefit from health promotion activities, as well as focus recruitment efforts for oncological and other clinical trials [10]. …”

Section: Introductionmentioning

confidence: 99%

Utilizing spatial statistics to identify cancer hot spots: a surveillance strategy to inform community-engaged outreach efforts

et al. 2014

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BackgroundUtilization of spatial statistics and Geographic Information Systems (GIS) technologies remain underrepresented in the community-engagement literature, despite its potential role in informing community outreach efforts and in identifying populations enthusiastic to participate in biomedical and health research. Such techniques are capable not only of examining the epidemiological relationship between the environment and a disease, but can also focus limited resources and strategically inform where on the landscape outreach efforts may be optimized.MethodsThese analyses present several spatial statistical techniques among the HealthStreet population, a community-engaged organization with aims to link underrepresented populations to medical and social care as well as opportunities to participate in University-sponsored research. Local Indicators of Spatial Association (LISA) and Getis-Ord Gi*(d) statistics are utilized to examine where cancer-related “hot spots” exist among minority and non-minority HealthStreet respondents within Alachua County, Florida, United States (US). Interest in research is also reported, by minority status and lifetime history of cancer.ResultsOverall, spatial clustering of cancer was observed to vary by minority status, suggesting disparities may exist among minorities and non-minorities in regards to where cancer is occurring. Specifically, significant hot spots of cancer were observed among non-minorities in more urban areas throughout Alachua County, Florida, US while more rural clusters were observed among minority members, specifically west and southwest of urban city limits.ConclusionsThese results may help focus future outreach efforts to include underrepresented populations in health research, as well as focus preventative and palliative oncological care. Further, global community engaged studies and community outreach efforts outside of the United States may use similar methods to focus limited resources and recruit underrepresented populations into health research.Electronic supplementary materialThe online version of this article (doi:10.1186/1476-072X-13-39) contains supplementary material, which is available to authorized users.

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“…Understanding with specificity where cancer burdens are concentrated has the potential to greatly enhance the efficiency of cancer prevention and control efforts. Geospatial mapping of population-based cancer registry data, used commonly in high-resource settings, has not been widely used in LMICs [ 14 ], with notable exceptions, primarily outside of SSA [ 15 - 20 ]. High-resolution cancer maps could provide clear targets for cancer prevention and control efforts in SSA and other low-resource settings, optimizing service delivery for maximal benefit.…”

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confidence: 99%

High-resolution disease maps for cancer control in low-resource settings: A spatial analysis of cervical cancer incidence in Kampala, Uganda

et al. 2022

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Background The global burden of cervical cancer is concentrated in low-and middle-income countries (LMICs), with the greatest burden in Africa. Targeting limited resources to populations with the greatest need to maximize impact is essential. The objectives of this study were to geocode cervical cancer data from a population-based cancer registry in Kampala, Uganda, to create high-resolution disease maps for cervical cancer prevention and control planning, and to share lessons learned to optimize efforts in other low-resource settings. Methods Kampala Cancer Registry records for cervical cancer diagnoses between 2008 and 2015 were updated to include geographies of residence at diagnosis. Population data by age and sex for 2014 was obtained from the Uganda Bureau of Statistics. Indirectly age-standardized incidence ratios were calculated for sub-counties and estimated continuously across the study area using parish level data. Results Overall, among 1873 records, 89.6% included a valid sub-county and 89.2% included a valid parish name. Maps revealed specific areas of high cervical cancer incidence in the region, with significant variation within sub-counties, highlighting the importance of high-resolution spatial detail. Conclusions Population-based cancer registry data and geospatial mapping can be used in low-resource settings to support cancer prevention and control efforts, and to create the potential for research examining geographic factors that influence cancer outcomes. It is essential to support LMIC cancer registries to maximize the benefits from the use of limited cancer control resources.

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An eight-year snapshot of geospatial cancer research (2002–2009): clinico-epidemiological and methodological findings and trends

Cited by 15 publications

References 145 publications

Contribution of Geographic Location to Disparities in Ovarian Cancer Treatment

Contribution of Geographic Location to Disparities in Ovarian Cancer Treatment

Utilizing spatial statistics to identify cancer hot spots: a surveillance strategy to inform community-engaged outreach efforts

High-resolution disease maps for cancer control in low-resource settings: A spatial analysis of cervical cancer incidence in Kampala, Uganda

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